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在短信卫生保健干预中使用生成性AI进行内容开发的行为:案例研究
Rachel M Harrison1, Ekaterina Lapteva2, Anton Bibin3
1GenAI Lab, Ophiuchus LLC, Dover, DE, United States.
JMIR AI
|October 15, 2024
概括
生成型人工智能 (AI) 为创建医疗保健干预信息提供了一种透明和高效的方法. 这种方法提供了人工智能生成的最大数据集,用于2型糖尿病患者的药物坚持.
科学领域:
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
- 数字健康干预措施 数字健康干预措施
背景情况:
- 简短信息干预在医疗保健方面显示出希望,但缺乏透明度和可访问的数据.
- 目前由研究人员驱动的内容创建是资源密集和低效的.
研究的目的:
- 展示SMS健康干预中有效和透明的内容创建的生成人工智能 (AI).
- 提供最大的公开可用的短信数据集和可复制的源代码.
主要方法:
- 使用GPT-3.5 (OpenAI) 来为2型糖尿病患者生成药物坚持信息.
- 采用了基于证据的行为改变技术和附属提示,遵守内容和短信标准.
主要成果:
- 创建了一个包含1150个简短信息的数据集,这是单个医疗保健干预措施中最大的数据集.
- 89.91%的消息符合字符长度要求,80.7%符合可读性标准.
- 人工智能生成的消息显示了与现有数据集相比的多样性.
结论:
- 生成型人工智能为医疗干预内容创建提供了一种新,高效的方法.
- 需要进一步的研究来评估AI产生的内容的伦理,安全和有效性标准.
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